Calculation of two-dimensional turbulent flow fields

Navier-Stokes equation solutions for two- dimensional turbulent flow fields of compressible viscous flui

Regional Cultures and the Psychological Geography of Switzerland: Person-Environment-Fit in Personality Predicts Subjective Wellbeing.

The present study extended traditional nation-based research on person-culture-fit to the regional level. First, we examined the geographical distribution of Big Five personality traits in Switzerland. Across the 26 Swiss cantons, unique patterns were observed for all traits. For Extraversion and Neuroticism clear language divides emerged between the French- and Italian-speaking South-West vs. the German-speaking North-East. Second, multilevel modeling demonstrated that person-environment-fit in Big Five, composed of elevation (i.e., mean differences between individual profile and cantonal profile), scatter (differences in mean variances) and shape (Pearson correlations between individual and cantonal profiles across all traits; Furr, 2008, 2010), predicted the development of subjective wellbeing (i.e., life satisfaction, satisfaction with personal relationships, positive affect, negative affect) over a period of 4 years. Unexpectedly, while the effects of shape were in line with the person-environment-fit hypothesis (better fit predicted higher subjective wellbeing), the effects of scatter showed the opposite pattern, while null findings were observed for elevation. Across a series of robustness checks, the patterns for shape and elevation were consistently replicated. While that was mostly the case for scatter as well, the effects of scatter appeared to be somewhat less robust and more sensitive to the specific way fit was modeled when predicting certain outcomes (negative affect, positive affect). Distinguishing between supplementary and complementary fit may help to reconcile these findings and future research should explore whether and if so under which conditions these concepts may be applicable to the respective facets of person-culture-fit

Can Music Increase Empathy? Interpreting Musical Experience Through the Empathizing–Systemizing (E-S) Theory: Implications for Autism

Recent research has provided evidence that musical interaction can promote empathy. Yet little is known about the underlying intrapersonal and social psychological processes that are involved when this occurs. For example, which types of music increase empathy and which types decrease it; what role, if any, does empathy play in determining individual differences in musical preference, perception, and performance; or, how do these psychological underpinnings help explain the musical experiences of people with autism spectrum conditions (ASC). To address these questions we employ the Empathizing–Systemizing (E-S) theory as a fruitful framework in which to understand these music-related phenomena. Specifically, we explore how individual differences in musical preference, perception, and performance can be explained by E-S theory. We provide examples from open-ended descriptions of strong musical experiences to demonstrate the ways in which empathy and music inter-relate. Importantly, we discuss the implications for the study of autism, and for how music therapists and clinicians can use music as a tool in their work with individuals diagnosed with ASC.

Happier People Live More Active Lives: Using Smartphones to Link Happiness and Physical Activity.

Physical activity, both exercise and non-exercise, has far-reaching benefits to physical health. Although exercise has also been linked to psychological health (e.g., happiness), little research has examined physical activity more broadly, taking into account non-exercise activity as well as exercise. We examined the relationship between physical activity (measured broadly) and happiness using a smartphone application. This app has collected self-reports of happiness and physical activity from over ten thousand participants, while passively gathering information about physical activity from the accelerometers on users' phones. The findings reveal that individuals who are more physically active are happier. Further, individuals are happier in the moments when they are more physically active. These results emerged when assessing activity subjectively, via self-report, or objectively, via participants' smartphone accelerometers. Overall, this research suggests that not only exercise but also non-exercise physical activity is related to happiness. This research further demonstrates how smartphones can be used to collect large-scale data to examine psychological, behavioral, and health-related phenomena as they naturally occur in everyday life.Engineering and Physical Sciences Research Council (UBhave project (Ubiquitous and Social Computing for Positive Behaviour Change, Grant ID: EP/I032673/1))This is the final version of the article. It first appeared from Public Library of Science via https://doi.org/http://dx.doi.org/10.1371/journal.pone.016058

Fear and deprivation in Trump’s America: A regional analysis of voting behavior in the 2016 and 2020 U.S. presidential elections

Since Trump was elected U.S. President in 2016, researchers have sought to explain his support, with some focusing on structural factors (e.g., economics) and others focusing on psychological factors (e.g., negative emotions). We integrate these perspectives in a regional analysis of 18+ structural variables capturing economic, demographic, and health factors as well as the aggregated neuroticism scores of 3+ million individuals. Results revealed that regions that voted for Trump in 2016 and 2020 had high levels of neuroticism and economic deprivation. Regions that voted for Trump also had high anti-Black implicit bias and low ethnic diversity, though Trump made gains in ethnically diverse regions in 2020. Trump’s voter base differed from the voter base of more traditional Republican candidates and Democrat Bernie Sanders. In sum, structural and psychological factors both explain Trump’s unique authoritarian appeal

Sequence multi-task learning to forecast mental wellbeing from sparse self-reported data

Smartphones have started to be used as self reporting tools for mental health state as they accompany individuals during their days and can therefore gather temporally fine grained data. However, the analysis of self reported mood data offers challenges related to non-homogeneity of mood assessment among individuals due to the complexity of the feeling and the reporting scales, as well as the noise and sparseness of the reports when collected in the wild. In this paper, we propose a new end-to-end ML model inspired by video frame prediction and machine translation, that forecasts future sequences of mood from previous self-reported moods collected in the real world using mobile devices. Contrary to traditional time series forecasting algorithms, our multi-task encoder-decoder recurrent neural network learns patterns from different users, allowing and improving the prediction for users with limited number of self-reports. Unlike traditional feature-based machine learning algorithms, the encoder-decoder architecture enables to forecast a sequence of future moods rather than one single step. Meanwhile, multi-task learning exploits some unique characteristics of the data (mood is bi-dimensional), achieving better results than when training single-task networks or other classifiers. Our experiments using a real-world dataset of 33, 000 user-weeks revealed that (i) 3 weeks of sparsely reported mood is the optimal number to accurately forecast mood, (ii) multi-task learning models both dimensions of mood –valence and arousal– with higher accuracy than separate or traditional ML models, and (iii) mood variability, personality traits and day of the week play a key role in the performance of our model. We believe this work provides psychologists and developers of future mobile mental health applications with a ready-to-use and effective tool for early diagnosis of mental health issues at scale.This work was supported by the Embiricos Trust Scholarship of Jesus College Cambridge, EPSRC through Grants DTP (EP/N509620/1) and UBHAVE (EP/I032673/1), and Nokia Bell Labs through the Centre of Mobile, Wearable Systems and Augmented Intelligence

Elevated empathy in adults following childhood trauma.

Traumatic events increase the risk of depression, but there is also evidence that adversity can lead to posttraumatic growth, including increased compassion and prosocial behavior. To date there is no empirical research pinpointing childhood trauma to an increase in trait empathy in adulthood. Although somewhat counter-intuitive, this might be predicted if trauma not only increases fear of future threat but also renders the individual more sensitive to suffering in others. We explored this possible link using multiple studies, self-report measures, and non-clinical samples. Results across samples and measures showed that, on average, adults who reported experiencing a traumatic event in childhood had elevated empathy levels compared to adults who did not experience a traumatic event. Further, the severity of the trauma correlated positively with various components of empathy. These findings suggest that the experience of a childhood trauma increases a person's ability to take the perspective of another and to understand their mental and emotional states, and that this impact is long-standing. Future research needs to test if this is seen on performance measures, and how these findings extend to clinical populations.Jaso

Personality maturation around the world:A cross-cultural examination of Social-Investment Theory

During early adulthood, individuals from different cultures across the world tend to become more agreeable, more conscientious, and less neurotic. Two leading theories offer different explanations for these pervasive age trends: Five-factor theory proposes that personality maturation is largely determined by genetic factors, whereas social-investment theory proposes that personality maturation in early adulthood is largely the result of normative life transitions to adult roles. In the research reported here, we conducted the first systematic cross-cultural test of these theories using data from a large Internet-based sample of young adults from 62 nations (N = 884,328). We found strong evidence for universal personality maturation from early to middle adulthood, yet there were significant cultural differences in age effects on personality traits. Consistent with social-investment theory, results showed that cultures with an earlier onset of adult-role responsibilities were marked by earlier personality maturation. Keywords: personality development, Big Five, social investment, culture, adult development, cross-cultural differences, personalit